2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

The European commission

Integrity is one criteria to evaluate GNSS performance, which was first introduced in the aviation field. It is a measure of trust which can be placed in the correctness of the information supplied by the total system. In recent years, many GNSS-based applications emerge in the urban environment including liability critical ones, so the concept of integrity attracts more and more attention from urban GNSS users. However, the algorithms developed for the aerospace domain cannot be introduced directly to the GNSS land applications. This is because a high data redundancy exists in the aviation domain and the hypothesis that only one failure occurs at a time is made, which is not the case for the urban users. The main objective of this paper is to provide an overview of the past and current literature discussing the GNSS integrity for urban transport applications so as to point out possible challenges faced by GNSS receivers in such scenario. Key differences between integrity monitoring scheme in aviation domain and urban transport field are addressed. And this paper also points out several open research issues in this field.

/pdf/gnss-position-integrity-in-urban-environments-a-review-of-1ved0w5512.pdf

GNSS Position Integrity in Urban Environments: A Review of Literature

Cyclostationarity: New trends and applications

GPS is one of the most widely used wireless systems. A GPS receiver has to lock on the satellite signals to calculate its position. The process of locking on the satellites is quite costly and requires hundreds of millions of hardware multiplications, leading to high power consumption. The fastest known algorithm for this problem is based on the Fourier transform and has a complexity of O(n log n), where n is the number of signal samples. This paper presents the fastest GPS locking algorithm to date. The algorithm reduces the locking complexity to O(n√(log n)). Further, if the SNR is above a threshold, the algorithm becomes linear, i.e., O(n). Our algorithm builds on recent developments in the growing area of sparse recovery. It exploits the sparse nature of the synchronization problem, where only the correct alignment between the received GPS signal and the satellite code causes their cross-correlation to spike.We further show that the theoretical gain translates into empirical gains for GPS receivers. Specifically, we built a prototype of the design using software radios and tested it on two GPS data sets collected in the US and Europe. The results show that the new algorithm reduces the median number of multiplications by 2.2x in comparison to the state of the art design, for real GPS signals.

/pdf/faster-gps-via-the-sparse-fourier-transform-3mlvnf8inj.pdf

Faster GPS via the sparse fourier transform

This paper considers interference suppression and multipath mitigation in Global Navigation Satellite Systems (GNSSs). In particular, a self-coherence anti-jamming scheme is introduced which relies on the unique structure of the coarse/acquisition (C/A) code of the satellite signals. Because of the repetition of the C/A-code within each navigation symbol, the satellite signals exhibit strong self-coherence between chip-rate samples separated by integer multiples of the spreading gain. The proposed scheme utilizes this inherent self-coherence property to excise interferers that have different temporal structures from that of the satellite signals. Using a multiantenna navigation receiver, the proposed approach obtains the optimal set of beamforming coefficients by maximizing the cross correlation between the output signal and a reference signal, which is generated from the received data. It is demonstrated that the proposed scheme can provide high gains toward all satellites in the field of view, while suppressing strong interferers. By imposing constraints on the beamformer, the proposed method is also capable of mitigating multipath that enters the receiver from or near the horizon. No knowledge of either the transmitted navigation symbols or the satellite positions is required.

A novel interference suppression scheme for global navigation satellite systems using antenna array

Positioning and navigation by GNSS in urban context are always challenging tasks, because of signal propagation problems such as shadowing effects and multipath. When not enough GNSS signals are received in line-of-sight (LOS), classical approaches mitigating multipath effects become insufficient because there is not enough reliable information available. Consequently, positioning errors can be about tens of meters, especially in urban canyons. In this paper, we introduce a GNSS positioning approach that uses constructively non-line-of-sight (NLOS) signals in order to have enough information to compute the user’s position. In this work, we use the SE-NAV software to predict the geometric paths of NLOS signals using a high realistic 3D model of the environment. More precisely, we propose a new version of the extended Kalman filter augmented by the information provided by SE-NAV, referred to as 3D AEKF, for GNSS navigation in NLOS context. In the proposed approach, the measurement model traditionally based on the trilateration equations is constructed from the received paths estimated by SE-NAV. The Jacobian of the measurement model is calculated through knowledge of the objects on which the reflections have occured. To use even less reliable measurements, we propose a robust version of the 3D AEKF. Simulations conducted in realistic scenarios allow the performance of the proposed method to be evaluated.

Tight Integration of GNSS and a 3D City Model for Robust Positioning in Urban Canyons

Multipath (MP) remains the main source of error when using global navigation satellite systems (GNSS) in a constrained environment, leading to biased measurements and thus to inaccurate estimated positions. This paper formulates the GNSS navigation problem as the resolution of an overdetermined system whose unknowns are the receiver position and speed, clock bias and clock drift, and the potential biases affecting GNSS measurements. We assume that only a part of the satellites are affected by MP, i.e., that the unknown bias vector has several zero components, which allows sparse estimation theory to be exploited. The natural way of enforcing this sparsity is to introduce an $\ell _{1}$ regularization associated with the bias vector. This leads to a least absolute shrinkage and selection operator problem that is solved using a reweighted- $\ell _{1}$ algorithm. The weighting matrix of this algorithm is designed carefully as functions of the satellite carrier-to-noise density ratio ( $C/N_{0}$ ) and the satellite elevations. Experimental validation conducted with real GPS data show the effectiveness of the proposed method as long as the sparsity assumption is respected.

/pdf/multipath-mitigation-for-gnss-positioning-in-an-urban-4udinkhq5r.pdf

Multipath Mitigation for GNSS Positioning in an Urban Environment Using Sparse Estimation

In this paper, we introduce a new approach for the acquisition of weak GNSS signals. For the GPS L1 signal, we utilize the replication property of the C/A code within each data bit to introduce a block averaging pre-processing (BAP) approach for improving receiver robustness against undesired signals. A large number of weighted signal blocks is coherently accumulated and synchronously averaged to obtain a single block with improved signal power. We present several properties of the proposed GNSS signals enhancement technique and we analyze its robustness against noise and different classes of interferers. Thus, we develop a software defined acquisition procedure using the efficient FFT correlation approach. We propose two acquisition algorithms based on the BAP approach. The first scheme implements the parallel code phase search in finding the 2-D spectrum peak using circular cross-correlations. In the second scheme, we exploit the BAP for a fast acquisition performing the frequency estimation prior to the 1-D code-phase search.

/pdf/acquisition-of-weak-gnss-signals-using-a-new-block-averaging-ez519yir10.pdf

Mohamed Sahmoudi

Papers

Tight Integration of GNSS and a 3D City Model for Robust Positioning in Urban Canyons

Multipath Mitigation for GNSS Positioning in an Urban Environment Using Sparse Estimation

Acquisition of weak GNSS signals using a new block averaging pre-processing

Robust tracking of weak GPS signals in multipath and jamming environments

Multipath mitigation techniques using maximum-likelihood principle